Triple

T6106160
Position Surface form Disambiguated ID Type / Status
Subject South Region E136121 entity
Predicate containsTown P847 FINISHED
Object Ntem
Ntem is a town located in the South Region of Cameroon.
 E573667 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ntem | Statement: [South Region, containsTown, Ntem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ntem
Context triple: [South Region, containsTown, Ntem]
  • A. Nembe
    Nembe is an Ijaw subgroup and town in Bayelsa State, Nigeria, known historically as a coastal trading center in the Niger Delta.
  • B. Oshindonga
    Oshindonga is a standardized Bantu language variety spoken primarily in northern Namibia and southern Angola, forming one of the main dialects of the Oshiwambo language cluster.
  • C. Eyamba
    Eyamba is a prominent clan of the Efik people of southeastern Nigeria, historically associated with leadership and influence in the Old Calabar region.
  • D. Tamba
    Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
  • E. Ndé
    Ndé is an administrative division (department) located in Cameroon's West Region, known for its predominantly Bamiléké population and highland rural communities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ntem
Triple: [South Region, containsTown, Ntem]
Generated description
Ntem is a town located in the South Region of Cameroon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ntem
Target entity description: Ntem is a town located in the South Region of Cameroon.
  • A. Nembe
    Nembe is an Ijaw subgroup and town in Bayelsa State, Nigeria, known historically as a coastal trading center in the Niger Delta.
  • B. Oshindonga
    Oshindonga is a standardized Bantu language variety spoken primarily in northern Namibia and southern Angola, forming one of the main dialects of the Oshiwambo language cluster.
  • C. Eyamba
    Eyamba is a prominent clan of the Efik people of southeastern Nigeria, historically associated with leadership and influence in the Old Calabar region.
  • D. Tamba
    Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
  • E. Ndé
    Ndé is an administrative division (department) located in Cameroon's West Region, known for its predominantly Bamiléké population and highland rural communities.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b806bd48190b6f020af3391adb8 completed March 22, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1415ce66081908c68088911f91854 completed March 23, 2026, 1:34 p.m.
NEDg Description generation batch_69c14c2ad33c8190b025a9a0df4d6a05 completed March 23, 2026, 2:20 p.m.
NED2 Entity disambiguation (via description) batch_69c14ccbbe548190a7dfcfbd1567bc81 completed March 23, 2026, 2:23 p.m.
Created at: March 22, 2026, 4:13 p.m.